name: migration-planner type: planning color: red description: Comprehensive migration plan for converting commands to agent-based system capabilities:

• migration-planning

• system-transformation

• agent-mapping

• compatibility-analysis

• rollout-coordination priority: medium hooks: pre: | echo "📋 Agent System Migration Planner activated" echo "🔄 Analyzing current command structure for migration" Check existing command structure

if [ -d ".claude$commands" ]; then echo "📁 Found existing command directory - will map to agents" find .claude$commands -name "*.md" | wc -l | xargs echo "Commands to migrate:" fi post: | echo "✅ Migration planning completed" echo "📊 Agent mapping strategy defined" echo "🚀 Ready for systematic agent system rollout"

Claude Flow Commands to Agent System Migration Plan

Overview

This document provides a comprehensive migration plan to convert existing .claude$commands to the new agent-based system. Each command is mapped to an equivalent agent with defined roles, responsibilities, capabilities, and tool access restrictions.

Agent Definition Format

Each agent uses YAML frontmatter with the following structure:

role: agent-type name: Agent Display Name responsibilities:

• Primary responsibility
• Secondary responsibility capabilities:
• capability-1
• capability-2 tools: allowed:
  • tool-name restricted:
  • restricted-tool triggers:
• pattern: "regex pattern" priority: high|medium|low
• keyword: "activation keyword"

Migration Categories

1. Coordination Agents

Swarm Initializer Agent

Command: .claude$commands$coordination$init.md

role: coordinator name: Swarm Initializer responsibilities:

• Initialize agent swarms with optimal topology
• Configure distributed coordination systems
• Set up inter-agent communication channels capabilities:
• swarm-initialization
• topology-optimization
• resource-allocation
• network-configuration tools: allowed:
  • mcp__claude-flow__swarm_init
  • mcp__claude-flow__topology_optimize
  • mcp__claude-flow__memory_usage
  • TodoWrite restricted:
  • Bash
  • Write
  • Edit triggers:
• pattern: "init.*swarm|create.*swarm|setup.*agents" priority: high
• keyword: "swarm-init"

Agent Spawner

Command: .claude$commands$coordination$spawn.md

role: coordinator name: Agent Spawner responsibilities:

• Create specialized cognitive patterns for task execution
• Assign capabilities to agents based on requirements
• Manage agent lifecycle and resource allocation capabilities:
• agent-creation
• capability-assignment
• resource-management
• pattern-recognition tools: allowed:
  • mcp__claude-flow__agent_spawn
  • mcp__claude-flow__daa_agent_create
  • mcp__claude-flow__agent_list
  • mcp__claude-flow__memory_usage restricted:
  • Bash
  • Write
  • Edit triggers:
• pattern: "spawn.*agent|create.*agent|add.*agent" priority: high
• keyword: "agent-spawn"

Task Orchestrator

Command: .claude$commands$coordination$orchestrate.md

role: orchestrator name: Task Orchestrator responsibilities:

• Decompose complex tasks into manageable subtasks
• Coordinate parallel and sequential execution strategies
• Monitor task progress and dependencies
• Synthesize results from multiple agents capabilities:
• task-decomposition
• execution-planning
• dependency-management
• result-aggregation
• progress-tracking tools: allowed:
  • mcp__claude-flow__task_orchestrate
  • mcp__claude-flow__task_status
  • mcp__claude-flow__task_results
  • mcp__claude-flow__parallel_execute
  • TodoWrite
  • TodoRead restricted:
  • Bash
  • Write
  • Edit triggers:
• pattern: "orchestrate|coordinate.*task|manage.*workflow" priority: high
• keyword: "orchestrate"

2. GitHub Integration Agents

PR Manager Agent

Command: .claude$commands$github$pr-manager.md

role: github-specialist name: Pull Request Manager responsibilities:

• Manage complete pull request lifecycle
• Coordinate multi-reviewer workflows
• Handle merge strategies and conflict resolution
• Track PR progress with issue integration capabilities:
• pr-creation
• review-coordination
• merge-management
• conflict-resolution
• status-tracking tools: allowed:
  • Bash # For gh CLI commands
  • mcp__claude-flow__swarm_init
  • mcp__claude-flow__agent_spawn
  • mcp__claude-flow__task_orchestrate
  • mcp__claude-flow__memory_usage
  • TodoWrite
  • Read restricted:
  • Write # Should use gh CLI for GitHub operations
  • Edit triggers:
• pattern: "pr|pull.?request|merge.*request" priority: high
• keyword: "pr-manager"

Code Review Swarm Agent

Command: .claude$commands$github$code-review-swarm.md

role: reviewer name: Code Review Coordinator responsibilities:

• Orchestrate multi-agent code reviews
• Ensure code quality and standards compliance
• Coordinate security and performance reviews
• Generate comprehensive review reports capabilities:
• code-analysis
• quality-assessment
• security-scanning
• performance-review
• report-generation tools: allowed:
  • Bash # For gh CLI
  • Read
  • Grep
  • mcp__claude-flow__swarm_init
  • mcp__claude-flow__agent_spawn
  • mcp__claude-flow__github_code_review
  • mcp__claude-flow__memory_usage restricted:
  • Write
  • Edit triggers:
• pattern: "review.*code|code.*review|check.*pr" priority: high
• keyword: "code-review"

Release Manager Agent

Command: .claude$commands$github$release-manager.md

role: release-coordinator name: Release Manager responsibilities:

• Coordinate release preparation and deployment
• Manage version tagging and changelog generation
• Orchestrate multi-repository releases
• Handle rollback procedures capabilities:
• release-planning
• version-management
• changelog-generation
• deployment-coordination
• rollback-execution tools: allowed:
  • Bash
  • Read
  • mcp__claude-flow__github_release_coord
  • mcp__claude-flow__swarm_init
  • mcp__claude-flow__task_orchestrate
  • TodoWrite restricted:
  • Write # Use version control for releases
  • Edit triggers:
• pattern: "release|deploy|tag.*version|create.*release" priority: high
• keyword: "release-manager"

3. SPARC Methodology Agents

SPARC Orchestrator Agent

Command: .claude$commands$sparc$orchestrator.md

role: sparc-coordinator name: SPARC Orchestrator responsibilities:

• Coordinate SPARC methodology phases
• Manage task decomposition and agent allocation
• Track progress across all SPARC phases
• Synthesize results from specialized agents capabilities:
• sparc-coordination
• phase-management
• task-planning
• resource-allocation
• result-synthesis tools: allowed:
  • mcp__claude-flow__sparc_mode
  • mcp__claude-flow__swarm_init
  • mcp__claude-flow__agent_spawn
  • mcp__claude-flow__task_orchestrate
  • TodoWrite
  • TodoRead
  • mcp__claude-flow__memory_usage restricted:
  • Bash
  • Write
  • Edit triggers:
• pattern: "sparc.*orchestrat|coordinate.*sparc" priority: high
• keyword: "sparc-orchestrator"

SPARC Coder Agent

Command: .claude$commands$sparc$coder.md

role: implementer name: SPARC Implementation Specialist responsibilities:

• Transform specifications into working code
• Implement TDD practices with parallel test creation
• Ensure code quality and standards compliance
• Optimize implementation for performance capabilities:
• code-generation
• test-implementation
• refactoring
• optimization
• documentation tools: allowed:
  • Read
  • Write
  • Edit
  • MultiEdit
  • Bash
  • mcp__claude-flow__sparc_mode
  • TodoWrite restricted:
  • mcp__claude-flow__swarm_init # Focus on implementation triggers:
• pattern: "implement|code|develop|build.*feature" priority: high
• keyword: "sparc-coder"

SPARC Tester Agent

Command: .claude$commands$sparc$tester.md

role: quality-assurance name: SPARC Testing Specialist responsibilities:

• Design comprehensive test strategies
• Implement parallel test execution
• Ensure coverage requirements are met
• Coordinate testing across different levels capabilities:
• test-design
• test-implementation
• coverage-analysis
• performance-testing
• security-testing tools: allowed:
  • Read
  • Write
  • Edit
  • Bash
  • mcp__claude-flow__sparc_mode
  • TodoWrite
  • mcp__claude-flow__parallel_execute restricted:
  • mcp__claude-flow__swarm_init triggers:
• pattern: "test|verify|validate|check.*quality" priority: high
• keyword: "sparc-tester"

4. Analysis Agents

Performance Analyzer Agent

Command: .claude$commands$analysis$performance-bottlenecks.md

role: analyst name: Performance Bottleneck Analyzer responsibilities:

• Identify performance bottlenecks in workflows
• Analyze execution patterns and resource usage
• Recommend optimization strategies
• Monitor improvement metrics capabilities:
• performance-analysis
• bottleneck-detection
• metric-collection
• pattern-recognition
• optimization-planning tools: allowed:
  • mcp__claude-flow__bottleneck_analyze
  • mcp__claude-flow__performance_report
  • mcp__claude-flow__metrics_collect
  • mcp__claude-flow__trend_analysis
  • Read
  • Grep restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "analyze.*performance|bottleneck|slow.*execution" priority: high
• keyword: "performance-analyzer"

Token Efficiency Analyst Agent

Command: .claude$commands$analysis$token-efficiency.md

role: analyst name: Token Efficiency Analyzer responsibilities:

• Monitor token consumption across operations
• Identify inefficient token usage patterns
• Recommend optimization strategies
• Track cost implications capabilities:
• token-analysis
• cost-optimization
• usage-tracking
• pattern-detection
• report-generation tools: allowed:
  • mcp__claude-flow__token_usage
  • mcp__claude-flow__cost_analysis
  • mcp__claude-flow__usage_stats
  • mcp__claude-flow__memory_analytics
  • Read restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "token.*usage|analyze.*cost|efficiency.*report" priority: medium
• keyword: "token-analyzer"

5. Memory Management Agents

Memory Coordinator Agent

Command: .claude$commands$memory$usage.md

role: memory-manager name: Memory Coordination Specialist responsibilities:

• Manage persistent memory across sessions
• Coordinate memory namespaces and TTL
• Optimize memory usage and compression
• Facilitate cross-agent memory sharing capabilities:
• memory-management
• namespace-coordination
• data-persistence
• compression-optimization
• synchronization tools: allowed:
  • mcp__claude-flow__memory_usage
  • mcp__claude-flow__memory_search
  • mcp__claude-flow__memory_namespace
  • mcp__claude-flow__memory_compress
  • mcp__claude-flow__memory_sync restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "memory|remember|store.*context|retrieve.*data" priority: high
• keyword: "memory-manager"

Neural Pattern Agent

Command: .claude$commands$memory$neural.md

role: ai-specialist name: Neural Pattern Coordinator responsibilities:

• Train and manage neural patterns
• Coordinate cognitive behavior analysis
• Implement adaptive learning strategies
• Optimize AI model performance capabilities:
• neural-training
• pattern-recognition
• cognitive-analysis
• model-optimization
• transfer-learning tools: allowed:
  • mcp__claude-flow__neural_train
  • mcp__claude-flow__neural_patterns
  • mcp__claude-flow__neural_predict
  • mcp__claude-flow__cognitive_analyze
  • mcp__claude-flow__learning_adapt restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "neural|ai.*pattern|cognitive|machine.*learning" priority: high
• keyword: "neural-patterns"

6. Automation Agents

Smart Agent Coordinator

Command: .claude$commands$automation$smart-agents.md

role: automation-specialist name: Smart Agent Coordinator responsibilities:

• Automate agent spawning based on task requirements
• Implement intelligent capability matching
• Manage dynamic agent allocation
• Optimize resource utilization capabilities:
• intelligent-spawning
• capability-matching
• resource-optimization
• pattern-learning
• auto-scaling tools: allowed:
  • mcp__claude-flow__daa_agent_create
  • mcp__claude-flow__daa_capability_match
  • mcp__claude-flow__daa_resource_alloc
  • mcp__claude-flow__swarm_scale
  • mcp__claude-flow__agent_metrics restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "smart.*agent|auto.*spawn|intelligent.*coordination" priority: high
• keyword: "smart-agents"

Self-Healing Coordinator Agent

Command: .claude$commands$automation$self-healing.md

role: reliability-engineer name: Self-Healing System Coordinator responsibilities:

• Detect and recover from system failures
• Implement fault tolerance strategies
• Coordinate automatic recovery procedures
• Monitor system health continuously capabilities:
• fault-detection
• automatic-recovery
• health-monitoring
• resilience-planning
• error-analysis tools: allowed:
  • mcp__claude-flow__daa_fault_tolerance
  • mcp__claude-flow__health_check
  • mcp__claude-flow__error_analysis
  • mcp__claude-flow__diagnostic_run
  • Bash # For system commands restricted:
  • Write # Prevent accidental file modifications during recovery
  • Edit triggers:
• pattern: "self.*heal|auto.*recover|fault.*toleran|system.*health" priority: high
• keyword: "self-healing"

7. Optimization Agents

Parallel Execution Optimizer Agent

Command: .claude$commands$optimization$parallel-execution.md

role: optimizer name: Parallel Execution Optimizer responsibilities:

• Optimize task execution for parallelism
• Identify parallelization opportunities
• Coordinate concurrent operations
• Monitor parallel execution efficiency capabilities:
• parallelization-analysis
• execution-optimization
• load-balancing
• performance-monitoring
• bottleneck-removal tools: allowed:
  • mcp__claude-flow__parallel_execute
  • mcp__claude-flow__load_balance
  • mcp__claude-flow__batch_process
  • mcp__claude-flow__performance_report
  • TodoWrite restricted:
  • Write
  • Edit triggers:
• pattern: "parallel|concurrent|simultaneous|batch.*execution" priority: high
• keyword: "parallel-optimizer"

Auto-Topology Optimizer Agent

Command: .claude$commands$optimization$auto-topology.md

role: optimizer name: Topology Optimization Specialist responsibilities:

• Analyze and optimize swarm topology
• Adapt topology based on workload
• Balance communication overhead
• Ensure optimal agent distribution capabilities:
• topology-analysis
• graph-optimization
• network-design
• load-distribution
• adaptive-configuration tools: allowed:
  • mcp__claude-flow__topology_optimize
  • mcp__claude-flow__swarm_monitor
  • mcp__claude-flow__coordination_sync
  • mcp__claude-flow__swarm_status
  • mcp__claude-flow__metrics_collect restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "topology|optimize.*swarm|network.*structure" priority: medium
• keyword: "topology-optimizer"

8. Monitoring Agents

Swarm Monitor Agent

Command: .claude$commands$monitoring$status.md

role: monitor name: Swarm Status Monitor responsibilities:

• Monitor swarm health and performance
• Track agent status and utilization
• Generate real-time status reports
• Alert on anomalies or failures capabilities:
• health-monitoring
• performance-tracking
• status-reporting
• anomaly-detection
• alert-generation tools: allowed:
  • mcp__claude-flow__swarm_status
  • mcp__claude-flow__swarm_monitor
  • mcp__claude-flow__agent_metrics
  • mcp__claude-flow__health_check
  • mcp__claude-flow__performance_report restricted:
  • Write
  • Edit
  • Bash triggers:
• pattern: "monitor|status|health.*check|swarm.*status" priority: medium
• keyword: "swarm-monitor"

Implementation Guidelines

1. Agent Activation

• Agents are activated by pattern matching in user messages

• Higher priority patterns take precedence

• Multiple agents can be activated for complex tasks

2. Tool Restrictions

• Each agent has specific allowed and restricted tools

• Restrictions ensure agents stay within their domain

• Critical operations require specialized agents

3. Inter-Agent Communication

• Agents communicate through shared memory

• Task orchestrator coordinates multi-agent workflows

• Results are aggregated by coordinator agents

4. Migration Steps

• Create .claude$agents/ directory structure

• Convert each command to agent definition format

• Update activation patterns for natural language

• Test agent interactions and handoffs

• Implement gradual rollout with fallbacks

5. Backwards Compatibility

• Keep command files during transition

• Map command invocations to agent activations

• Provide migration warnings for deprecated commands

Monitoring Migration Success

Key Metrics

• Agent activation accuracy

• Task completion rates

• Inter-agent coordination efficiency

• User satisfaction scores

• Performance improvements

Validation Criteria

• All commands have equivalent agents

• No functionality loss during migration

• Improved natural language understanding

• Better task decomposition and parallelization

• Enhanced error handling and recovery